The detrimental effect of rainforest conversion to rubber plantations on soil dissolved organic carbon and C: N stoichiometry, mediated by altered soil biogeochemistry.

Rainforest conversion into rubber (Hevea brasiliensis) plantations (RP) alters global carbon cycling and contributes to climate change. However, the impact of this widespread tropical land use change on various elements of the carbon cycle is poorly understood. Here, we aimed to investigate the impact of rainforest conversion into RP on soil-dissolved organic carbon (DOC), one of the most mobile organic matter (OM) in the terrestrial ecosystem that causes the transformation and migration of C. We also explored the underlying edaphic factors regulating soil DOC changes. Our study sites were rubber monoculture, mixed-rubber plantations (H. brasiliensis, Ficus langkokensis, and Actinodaphne henryi), and a reference rainforest. We found that soil DOC concentration was 150-200% higher in RP than in rainforests, with an unchanged pattern across the seasons (dry and rainy) and plantation type. These results were concomitant with degradation in main soil properties, markedly including lower pH, electrical conductivity, SOC, available nitrogen, available phosphorus, total nitrogen (TN), and total phosphorus (TP), following the RP establishment and explicitly having a significant negative correlation with DOC. Our fitted structure equation model (SEM) highlights that RP caused accelerated DOC production and a higher DOC/DN ratio by decreasing SOC (38.5%) and nutrients (TN and TP). Further, the SEM revealed a significant negative correlation between microbial biomass C (MBC) and N (MBN) and the DOC/DN ratio, implying limited microbial degradation of DOC under RP. This is further supported by our findings of 81.1% lower MBC per unit DOC and 37.1% lower MBN per unit DN under RP compared to rainforests, indicating poor transformation of DOC to microbial biomass under RP. Collectively, our findings suggest that RP with high nutrient demands and altered soil properties lead to increased leaching of DOC due to its limited utilization by microbes. These findings underscore the importance of robust and sustainable soil management (such as optimizing plant density and legume intercropping) in RP to improve soil health and minimize DOC leaching and its potential environmental consequences.

Evaluation of outcomes of clinical phenotyping-based treatment for bladder pain syndrome/interstitial cystitis.

Introduction: Bladder pain syndrome/Interstitial cystitis (BPS/IC) is clinically of diverse types because different causes contribute to the development of their symptoms. It is important to classify patients into various groups based on the possible etiopathogenesis of their condition. Treatment may be tailored to each specific group according to the possible cause. Methodology: Twenty-five patients diagnosed with BPS/IC were categorized into four different clinical phenotypes (CP) based on their history of symptoms, allergy, dysfunctional voiding, neuropathic pain, and the presence of Hunner's ulcer. Some patients could be classified into multiple groups. The patients were given oral pentosan polysulfate, and treatment specific to their CP. Patients in CP1, CP2, and CP3 groups received, respectively hydroxyzine, clonazepam, and amitriptyline. Patients with Hunner's lesions (HL) (CP4) underwent hydro distension and ablation of the lesion, followed by intravesical instillation of heparin and hydrocortisone. The patients were evaluated using the Apollo clinical scoring (ACS) system and their clinical scores were recorded at 1, 3, and 6 month(s). Results: Among the 25 patients, 5, 7, 4, and 9 patients were classified into CP 1 - CP4 groups respectively, and were all subjected to ACS assessment. In CP1 group (allergy group), 80% (4/5) of patients responded well to the treatment and 20% (1/5) had unsatisfactory responses. In CP2 group (dysfunctional voiding group), 71.42% (5/7) patients had good, and 28.57% (2/7) had excellent responses. In CP3 group (neuropathic pain group), 28.57% (3/4) patients had excellent, and 75% (1/4) patients had good responses. In CP4 group (HL group), 33.33% (3/9) patients had unsatisfactory, 44.44% (4/9) achieved good, and 22.22% (2/9) had excellent responses. Overall, 16% (4/25) patients had unsatisfactory, 56% (14/25) attained good, and 28% (7/25) had an excellent response at the completion of the study. Conclusion: Using clinical phenotyping-based features indicative of etiology could potentially improve treatment outcomes by targeting the specific pathological processes contributing to the patients' symptoms.

Admixture in the fungal pathogen Blastomyces.

Blastomyces is an emerging primary fungal pathogen that affects patients worldwide. The evolutionary processes that have resulted in the current diversity in the genus remain largely unexplored. We used whole genome sequences from 99 Blastomyces isolates, including two sequenced in this study using long-read technologies, to infer the phylogenetic relationships between Blastomyces species. We find that five different methods infer five different phylogenetic trees. Additionally, we find gene tree discordance along the genome with differences in the relative phylogenetic placement of several species of Blastomyces, which we hypothesize is caused by introgression. Our results suggest the urgent need to systematically collect Blastomyces samples around the world and study the evolutionary processes that govern intra- and interspecific variation in these medically important fungi.

Bisphenol A-induced oxidative stress increases the production of ovarian cancer stem cells in mice.

Bisphenol A (BPA) belongs to the endocrine disruptor chemicals (EDCs) causing various reproductive disorders in females. We analysed the toxic effects of BPA in the uterus and ovaries. The BPA was administered orally with the repeated low dose (LD, 1 mg/kg) and high dose (HD, 5 mg/kg) of body weight on alternate days for 4 months via oral gavage to Swiss mice. BPA administration decreases body weight, ovarian weight and size at LD, but increases ovarian weight and size at HD. The uterus weight, length, and diameter were increased in both the treated groups. The histopathological data show decreased ovarian follicle size, epithelial hyperplasia, and lymphocytic infiltration in the ovary. The BPA-treated uterus shows increased vascularization, atrophied endometrium and myometrium, and endometrial hyperplasia (EH) with aberrant glandular growth. The cancer stem cells (CSCs) in the ovaries were identified based on staining with anti-mouse CD44 and anti-mouse CD133 antibodies and analysed by flow cytometry. Three different populations of ovarian CSCs: CD44+CD133-, CD44+CD133+, and CD44-CD133+, can be recognised based on the intensity of these receptors. CD44+CD133- and CD44+CD133+ cell percentages were increased in BPA-treated groups. CD44-CD133+ were increased in LD but decreased in HD. The BPA administration also induces ROS production, which decreases the expression of antioxidant genes Superoxide dismutase 1 (SOD1), Superoxide dismutase 2 (SOD2), Catalase (CAT), Glutathione peroxidase 1 (GPX1), and Forkhead box O3 (FOXO3) in ovarian cells. In conclusion, BPA exposure induced an inflammatory response, increased CSC proportions, induced ROS, and decreased antioxidant responses in the ovaries.

Upcycling of industrial pea starch by rapid spray nanoprecipitation to develop plant-derived oil encapsulated starch nanoparticles for potential agricultural applications.

Starch is one of the natural encapsulant materials widely used in food, pharmaceutical and cosmetic industries. Starch with high amylose content (above 40 %, w/w) is prone to form single helices V-type allomorph with a hydrophilic outer surface and a hydrophobic inner cavity making them suitable for encapsulation of hydrophobic compounds such as essential oils, fatty acids, and vitamins. Pea starch obtained from pea protein processing industries have a high amylose content (40 %, w/w) rendering them unsuitable for direct food applications as ingredients. Therefore, in this study, an in-house spraying procedure was used to synthesize nanoparticles using pea starch, to encapsulate neem oil, a natural antimicrobial compound obtained from neem plant (Azadirachta indica) seed. The synthesis of the oil-encapsulated starch nanoparticles (OESNP) was optimized using a Box-Behnken experimental design to study the influence of the processing parameters such as the initial starch concentration, homogenization speed, duration of homogenization, sample injection rate, and quantity of antisolvent (ethanol). The optimized sample showed an 80-90 % encapsulation efficiency and particle size of <500 nm. The spherical OESNPs also demonstrated sustained release of the oil compared to free oil when dispersed in water. X-ray diffraction analysis revealed the coexistence of C-type and V-type polymorphs in the loaded and unloaded nanoparticles. It is concluded that the synthesized OESNPs with controlled release hold the potential to utilize industrial pea starch waste for the delivery of natural pesticides in agriculture.

An ITO free All Tungsten-Based Electrochromic Energy Storage Device as Smart Window.

Excessive electricity usage in buildings, notably for heating and cooling, accounts for over 30% of energy consumption, creating a pressing need for energy-saving solutions. Electrochromic Smart Windows (ECSW) aims to reduce energy use while maintaining comfort but faces high costs due to materials like tin-doped indium oxide (ITO) and thick electrochromic films. Moreover, achieving full opacity in the colored state of ECSW is a bottleneck for the industry to overcome privacy concerns. Herein, efforts are directed toward finding cost-efficient alternatives, with all-tungsten-based mesh networks showing promise due to enhanced stability. This newly developed ITO-free, all-tungsten ECSW displays minimal transmittance (≈3%) in the colored state using only 260 nm thick sub-stoichiometric tungsten oxide (WO3-x) film within a lithium-ion-based electrolyte. The ECSW device of size (25 cm2) also demonstrates areal capacitance of ≈13 mF cm-2 to power a liquid crystal display (LCD) for ≈25 min, showcasing its energy storage capabilities. Additionally, to confirm scalability and cost-effectiveness, a larger 15 × 15 cm2 ECSW utilized a single hybrid electrode, highlighting the potential for reducing costs when scaling up production processes. This advancement represents a significant stride toward accessible and energy-efficient smart window technology, offering broader applicability within modern architectural practices.

Genome editing prospects for heat stress tolerance in cereal crops.

The world population is steadily growing, exerting increasing pressure to feed in the future, which would need additional production of major crops. Challenges associated with changing and unpredicted climate (such as heat waves) are causing global food security threats. Cereal crops are a staple food for a large portion of the world's population. They are mostly affected by these environmentally generated abiotic stresses. Therefore, it is imperative to develop climate-resilient cultivars to support the sustainable production of main cereal crops (Rice, wheat, and maize). Among these stresses, heat stress causes significant losses to major cereals. These issues can be solved by comprehending the molecular mechanisms of heat stress and creating heat-tolerant varieties. Different breeding and biotechnology techniques in the last decade have been employed to develop heat-stress-tolerant varieties. However, these time-consuming techniques often lack the pace required for varietal improvement in climate change scenarios. Genome editing technologies offer precise alteration in the crop genome for developing stress-resistant cultivars. CRISPR/Cas9 (Clustered regularly interspaced short palindromic repeat/Cas9), one such genome editing platform, recently got scientists' attention due to its easy procedures. It is a powerful tool for functional genomics as well as crop breeding. This review will focus on the molecular mechanism of heat stress and different targets that can be altered using CRISPR/Cas genome editing tools to generate climate-smart cereal crops. Further, heat stress signaling and essential players have been highlighted to provide a comprehensive overview of the topic.

Study of resistance mechanism of Alternaria blight (Alternaria brassicicola) by biochemical markers in Indian Mustard (Brassica juncea L. Czern. &Coss.).

Indian mustard (Brassica juncea) is an important oilseed crop in India. Alternaria leaf spot (Alternaria blight) is incited by the fungus Alternaria brassicicola. It majorly affects crop production leading to a yield loss of up to 70%. To circumvent this problem, the study of the resistance mechanism and identification of biochemical markers is one of the important strategies for its management. In the present study, a total of 219 genotypes of Indian mustard with check were screened for Alternaria blight over two seasons. Based on the area under the disease progress curve (AUDPC) scores, ten consistently performing genotypes were selected for the screening of biochemical and yield attributes under artificial inoculated conditions of Alternaria brassicicola (Berk) Sacc. The result showed a negative correlation between disease and yield attributes. The catalase (CAT) activity was significantly increased in resistant genotypes compared to susceptible ones, indicating the crucial role of CAT in the resistance mechanism. Pathogen infection also increases the total protein content and the Alternaria-resistant genotype showed the highest total soluble protein while the susceptible genotype showed the lowest total soluble protein. The ten genotypes were categorized by SSI (stress susceptibility index) and Varuna was identified as a tolerant genotype and Giriraj as a susceptible genotype for Alternaria brassicicola (Berk) Sacc. Varuna and Giriraj were chosen for quantitative analysis of methionine and tryptophan amino acids from seeds using RP-HPLC (Reverse Phase-High Performance Liquid Chromatography) and there were significant differences in the levels of methionine and tryptophan between the Varuna and Giriraj genotypes. Varuna showed higher methionine and tryptophan content compared to the Giriraj genotype. Higher protein content demonstrated an increase in biotic stress-responsive amino acids, such as methionine and tryptophan, suggesting increased resistance to Alternaria diseases in these high-protein genotypes. These amino acids could be used as biochemical markers for Alternaria resistance of mustard.

Role of plasma exchange in a post-partum case of severe thrombotic thrombocytopenic purpura with acute kidney injury.

Thrombotic thrombocytopenic purpura (TTP) is a life-threatening disease present with the classic pentad of microangiopathic hemolytic anemia (MAHA), fever, neurologic changes, thrombocytopenia, and renal dysfunction. In a diagnostic dilemma, therapeutic plasma exchange (TPE) is a choice of life-saving intervention. In this, we assess the efficacy of TPE in a suspected case of post-partum TTP. A 27 years old female was admitted in an emergency on day 8 after a lower segment cesarian section (LSCS) with unresponsive behavior for 3 days and with TTP. She was normal 32 days back with her second, 7-month pregnancy. Ultrasonography (USG) showed an umbilical cord around the neck of the baby. On the fifth post-operative day, she was shifted to emergency with fever, generalized anasarca, gastrointestinal tract (GI) bleeding, low platelet count, and low Hb, with a poor Glasgow coma scale (GCS) of 6. On the bases of serum urea and serum creatinine, she presented acute kidney injury with encephalopathy. At emergency, she was unresponsive to mechanical ventilation and supportive treatment; hence, therapeutic plasma exchange was performed. After eight TPE cycles, the patient presented with an improved hematological and renal profile with good GCS. TPE is helpful and life-saving for suspected TTP patients with AKI.

Electrochromic and Energy Storage Performance Enhancement by Introducing Jahn-Teller Distortion: Experimental and Theoretical Study.

Aqueous electrochromic batteries (ECBs) have recently garnered significant attention within the realm of renewable rechargeable technology due to their potential applicability in diverse multifunctional devices featuring visible-level indicator batteries. However, there exists an imperative to comprehend the underlying structural factors that contribute to achieving an elevated electrochemical performance. In this context, we have synthesized and compared WO3·H2O (HWO) specifically for heightened ECB application as against the performance of a standard anhydrous WO3 (AWO). To unravel the underlying cause, a density functional theory (DFT) investigation is carried out, disclosing a structural deformation of HWO, unlike AWO, due to Jahn-Teller distortion induced by the presence of interlayer water. It results in a fully compatible HWO ion host to devise a zinc-ion aqueous electrolyte electrochromic battery, exhibiting superior redox reactivity, optical modulation (50%), capacity (200 mAh/m2), and cyclic stability. To glean insights into the dynamic structural alterations during the intercalation and deintercalation processes of Zn2+, ex situ X-ray diffraction and Raman spectroscopic studies are carried out. These investigations culminate in the determination that HWO films are better suited for the application than their AWO counterparts. This finding holds promise for advancing the applications of ECBs and represents a significant step forward in this field.

Anthropogenic restoration exhibits more complex and stable microbial co-occurrence patterns than natural restoration in rubber plantations.

Forest restoration is an effective method for restoring degraded soil ecosystems (e.g., converting primary tropical forests into rubber monoculture plantations; RM). The effects of forest restoration on microbial community diversity and composition have been extensively studied. However, how rubber plantation-based forest restoration reshapes soil microbial communities, networks, and inner assembly mechanisms remains unclear. Here, we explored the effects of jungle rubber mixed (JRM; secondary succession and natural restoration of RM) plantation and introduction of rainforest species (AR; anthropogenic restoration established by mimicking the understory and overstory tree species of native rainforests) to RM stands on soil physico-chemical properties and microbial communities. We found that converting tropical rainforest (RF) to RM decreased soil fertility and simplified microbial composition and co-occurrence patterns, whereas the conversion of RM to JRM and AR exhibited opposite results. These changes were significantly correlated with pH, soil moisture content (SMC), and soil nutrients, suggesting that vegetation restoration can provide a favorable soil microenvironment that promotes the development of soil microorganisms. The complexity and stability of the bacterial-fungal cross-kingdom, bacterial, and fungal networks increased with JRM and AR. Bacterial community assembly was primarily governed by stochastic (78.79 %) and deterministic (59.09 %) processes in JRM and AR, respectively, whereas stochastic processes (limited dispersion) predominantly shaped fungal assembly across all forest stands. AR has more significant benefits than JRM, such as a relatively slower and natural vegetation succession with more nutritive soil conditions, microbial diversity, and complex and stable microbial networks. These results highlight the importance of sustainable forest management to restore soil biodiversity and ecosystem functions after extensive soil degradation and suggest that anthropogenic restoration can more effectively improve soil quality and microbial communities than natural restoration in degraded rubber plantations.

Exploring the impact of high pressure processing on the characteristics of processed fruit and vegetable products: a comprehensive review.

Consumers are increasingly interested in additive-free products with a fresh taste, leading to a growing trend in high pressure processing (HPP) as an alternative to thermal processing. This review explores the impact of HPP on the properties of juices, smoothies, and purees, as well as its practical applications in the food industry. Research findings have explained that HPP is a most promising technology in comparison to thermal processing, in two ways i.e., for ensuring microbial safety and maximum retention of micro and macro nutrients and functional components. HPP preserves natural color and eliminates the need for artificial coloring. The review also emphasizes its potential for enhancing flavor in the beverage industry. The review also discusses how HPP indirectly affects plant enzymes that cause off-flavors and suggests potential hurdle approaches for enzyme inactivation based on research investigations. Scientific studies regarding the improved quality insights on commercially operated high pressure mechanisms concerning nutrient retention have paved the way for upscaling and boosted the market demand for HPP equipment. In future research, the clear focus should be on scientific parameters and sensory attributes related to consumer acceptability and perception for better clarity of the HPP effect on juice and smoothies/purees.

A safe, cost-effective, and high-throughput SARS-CoV-2 antigen capture ELISA suitable for large-scale screening in low-resource settings.

Diagnostics employing multiple modalities have been essential for controlling and managing COVID-19, caused by SARS-CoV-2. However, scaling up Reverse Transcription-Quantitative Polymerase Chain Reaction (RT-qPCR), the gold standard for SARS-CoV-2 detection, remains challenging in low and middle-income countries. Cost-effective and high-throughput alternatives like enzyme-linked immunosorbent assay (ELISA) could address this issue. We developed an in-house SARS-CoV-2 nucleocapsid capture ELISA, and validated on 271 nasopharyngeal swab samples from humans (n = 252), bovines (n = 10), and dogs (n = 9). This ELISA has a detection limit of 195 pg/100 µL of nucleocapsid protein and does not cross-react with related coronaviruses, ensuring high specificity to SARS-CoV-2. Diagnostic performance was evaluated using receiver operating characteristic curve analysis, showing a diagnostic sensitivity of 67.78 % and specificity of 100 %. Sensitivity improved to 74.32 % when excluding positive clinical samples with RT-qPCR Ct values > 25. Furthermore, inter-rater reliability analysis demonstrated substantial agreement (κ values = 0.73-0.80) with the VIRALDTECT II Multiplex RT-qPCR kit and perfect agreement with the CoVeasy™ COVID-19 rapid antigen self-test (κ values = 0.89-0.93). Our findings demonstrated that the in-house nucleocapsid capture ELISA is suitable for SARS-CoV-2 testing in humans and animals, meeting the necessary sensitivity and specificity thresholds for cost-effective, large-scale screening.

Redox Potential Based Self-Powered Electrochromic Devices for Smart Windows.

Energy-efficient glass windows are pivotal in modern infrastructure striving toward the "Zero energy" concept. Electrochromic (EC) energy storage devices emerge as a promising alternative to conventional glass, yet their widespread commercialization is impeded by high costs and dependence on external power sources. Addressing this, redox potential-based self-powered electrochromic (RP-SPEC) devices are introduced leveraging established EC materials like tungsten oxide (WO3) and vanadium-doped nickel oxide (V-NiO) along with aluminum (Al) as an anode. These devices produce open circuit voltages (OCV) exceeding ±0.3 V, enabling autonomous operation for multiple cycles. The WO3 film exhibits 1% transmission and 88% modulation in the colored state at 550 nm with a mere 260 nm thickness. The redox interactions facilitate coloring and bleaching cycles without external power, while photo-charging rejuvenates the system. Notably, the inherent voltages of the RP-SPEC device offer dual functionality, powering electronic devices for up to 81 h. Large-area (≈28 cm2) device feasibility is demonstrated, paving the way for industrial adoption. The RP-SPEC device promises to revolutionize smart window technology by offering both energy efficiency and autonomous operation, thus advancing sustainable infrastructure.

Comparative Antioxidant Activity and Untargeted Metabolomic Analyses of Sour Cherry Cultivars Based on Ultra-Performance-Time of Flight-Mass Spectrometry.

This study was conducted for the comparative analysis of antioxidant activity and untargeted metabolomics of dark- and light-colored sour cherry cultivars grown in Canada. Based on our previous study, we selected four cultivars-'Heimann R', 'Gorsemska', V70142, and 'Montmorency'-to determine the untargeted metabolites and their role in antioxidant activities. A total of 473 metabolites were identified from four sour cherry genotypes using UPLC-ToF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP > 1.0) in partial least-squares-discriminant analysis described 20 biomarker metabolites representing the cherry metabolome profiles. A heatmap of Pearson's correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. TPC and TAC were evaluated using the Folin-Ciocalteu method. The total antioxidant activity was performed using three different assays (ABTS, FRAP, and DPPH). This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

REST-dependent downregulation of von Hippel-Lindau tumor suppressor promotes autophagy in SHH-medulloblastoma.

The RE1 silencing transcription factor (REST) is a driver of sonic hedgehog (SHH) medulloblastoma genesis. Our previous studies showed that REST enhances cell proliferation, metastasis and vascular growth and blocks neuronal differentiation to drive progression of SHH medulloblastoma tumors. Here, we demonstrate that REST promotes autophagy, a pathway that is found to be significantly enriched in human medulloblastoma tumors relative to normal cerebella. In SHH medulloblastoma tumor xenografts, REST elevation is strongly correlated with increased expression of the hypoxia-inducible factor 1-alpha (HIF1α)-a positive regulator of autophagy, and with reduced expression of the von Hippel-Lindau (VHL) tumor suppressor protein - a component of an E3 ligase complex that ubiquitinates HIF1α. Human SHH-medulloblastoma tumors with higher REST expression exhibit nuclear localization of HIF1α, in contrast to its cytoplasmic localization in low-REST tumors. In vitro, REST knockdown promotes an increase in VHL levels and a decrease in cytoplasmic HIF1α protein levels, and autophagy flux. In contrast, REST elevation causes a decline in VHL levels, as well as its interaction with HIF1α, resulting in a reduction in HIF1α ubiquitination and an increase in autophagy flux. These data suggest that REST elevation promotes autophagy in SHH medulloblastoma cells by modulating HIF1α ubiquitination and stability in a VHL-dependent manner. Thus, our study is one of the first to connect VHL to REST-dependent control of autophagy in a subset of medulloblastomas.

Investigating the Presence of Rotavirus in Wastewater Samples of Bhopal Region, India, by Utilizing Droplet Digital Polymerase Chain Reaction.

INTRODUCTION: Rotavirus-induced viral gastroenteritis outbreaks result in over two million hospitalizations globally yearly. Wastewater-based epidemiology (WBE) has emerged as a crucial tool for detecting and monitoring viral outbreaks. The adoption of WBE has been instrumental in the early detection and surveillance of such viral outbreaks, providing a non-invasive method to assess public health. OBJECTIVE: This study aims to utilize droplet digital polymerase chain reaction (ddPCR) technology to detect and quantify Rotavirus in wastewater samples collected from the Bhopal region of India, thereby contributing to the understanding and management of viral gastroenteritis outbreaks through environmental surveillance. METHODS: In this study, we used ddPCR to detect and quantify Rotavirus in wastewater samples collected from the Bhopal region of India. We monitored its viral presence in municipal sewage treatment plants bi-weekly using an advanced ddPCR assay. Targeting the rotavirus non-structural protein 3 (NSP-3) region with custom primers and TaqMan probes, we detected virus concentration employing polyethylene glycol (PEG). Following RNA isolation, complementary DNA (cDNA) synthesis, and ddPCR analysis, our novel method eliminated standard curve dependence, propelling virus research and treatment forward. RESULTS: Out of the 42 samples collected, a 16.60% positivity rate was observed, indicating a moderate presence of Rotavirus in Bhopal. The wastewater treatment plants (WWTP) attached to a hospital exhibited a 42.85% positivity rate, indicating the need for targeted monitoring. Leveraging ddPCR, precise quantification of rotavirus concentrations (ranging from 0.75 to 28.9 copies/µL) facilitated understanding and supported effective remediation. CONCLUSIONS:  This study emphasizes the importance of vigilant wastewater surveillance, especially in WWTPs with higher rotavirus prevalence. The significance of ddPCR in comparison to conventional and real-time PCR lies in its superior sensitivity and specificity in detecting and quantifying positive samples. Furthermore, it can identify positive samples even in the smallest quantities without the need for a standard curve to evaluate. This makes ddPCR a valuable tool for accurate and precise detection and quantification of samples.

Advancing post-traumatic seizure classification and biomarker identification: Information decomposition based multimodal fusion and explainable machine learning with missing neuroimaging data.

A late post-traumatic seizure (LPTS), a consequence of traumatic brain injury (TBI), can potentially evolve into a lifelong condition known as post-traumatic epilepsy (PTE). Presently, the mechanism that triggers epileptogenesis in TBI patients remains elusive, inspiring the epilepsy community to devise ways to predict which TBI patients will develop PTE and to identify potential biomarkers. In response to this need, our study collected comprehensive, longitudinal multimodal data from 48 TBI patients across multiple participating institutions. A supervised binary classification task was created, contrasting data from LPTS patients with those without LPTS. To accommodate missing modalities in some subjects, we took a two-pronged approach. Firstly, we extended a graphical model-based Bayesian estimator to directly classify subjects with incomplete modality. Secondly, we explored conventional imputation techniques. The imputed multimodal information was then combined, following several fusion and dimensionality reduction techniques found in the literature, and subsequently fitted to a kernel- or a tree-based classifier. For this fusion, we proposed two new algorithms: recursive elimination of correlated components (RECC) that filters information based on the correlation between the already selected features, and information decomposition and selective fusion (IDSF), which effectively recombines information from decomposed multimodal features. Our cross-validation findings showed that the proposed IDSF algorithm delivers superior performance based on the area under the curve (AUC) score. Ultimately, after rigorous statistical comparisons and interpretable machine learning examination using Shapley values of the most frequently selected features, we recommend the two following magnetic resonance imaging (MRI) abnormalities as potential biomarkers: the left anterior limb of internal capsule in diffusion MRI (dMRI), and the right middle temporal gyrus in functional MRI (fMRI).

A Multiple Controlled Toffoli Driven Adaptive Quantum Neural Network Model for Dynamic Workload Prediction in Cloud Environments.

The key challenges in cloud computing encompass dynamic resource scaling, load balancing, and power consumption. Accurate workload prediction is identified as a crucial strategy to address these challenges. Despite numerous methods proposed to tackle this issue, existing approaches fall short of capturing the high-variance nature of volatile and dynamic cloud workloads. Consequently, this paper introduces a novel model aimed at addressing this limitation. This paper presents a novel Multiple Controlled Toffoli-driven Adaptive Quantum Neural Network (MCT-AQNN) model to establish an empirical solution to complex, elastic as well as challenging workload prediction problems by optimizing the exploration, adaption, and exploitation proficiencies through quantum learning. The computational adaptability of quantum computing is ingrained with machine learning algorithms to derive more precise correlations from dynamic and complex workloads. The furnished input data point and hatched neural weights are refitted in the form of qubits while the controlling effects of Multiple Controlled Toffoli (MCT) gates are operated at the hidden and output layers of Quantum Neural Network (QNN) for enhancing learning capabilities. Complimentarily, a Uniformly Adaptive Quantum Machine Learning (UAQL) algorithm has evolved to functionally and effectually train the QNN. The extensive experiments are conducted and the comparisons are performed with state-of-the-art methods using four real-world benchmark datasets. Experimental results evince that MCT-AQNN has up to 32%-96% higher accuracy than the existing approaches.

Rice crop residue management by the microbial consortium for rapid decomposition of straw.

Globally, more than 5 billion tons of crop residue (mainly rice straw) are produced yearly, and their management results in pollution, which kills microbes and limits soil nutrient recycling. Therefore, on-farm management that boosts degradation speed will improve the practicability of crop residue retention practices. The present study evaluated the 21 microbial isolates (Pseudomonas, Bacillus, Aspergillus, Trichoderma, Fusarium, and Rhizopus) from the soil of different agroclimatic zones obtained from rice fields for in situ straw degradation. The microbial diversity of these isolates was analyzed using 16 s rRNA and 18 s rRNA primers from various soil samples. The rice straw was used for degradation from isolated pathogens individually and in combination, and the results were analyzed using FTIR (Fourier transform infrared spectroscopy). The result suggested that the straw's degradation was the maximum with Trichoderma and Aspergillus, followed by the mixture of the isolates (Pseudomonas, Bacillus, Aspergillus, Trichoderma, Fusarium, and Rhizopus). Furthermore, SEM (scanning electron microscope) observed the degradation rate on different days of inoculation (7, 14, 28, 56, 70, and 100 DAI). The results showed that 90 DAI caused the highest degradation of rice straw. Therefore, Trichoderma containing microbial consortia could be used for vermicompost production from rice straw in field conditions, and it could increase crop productivity. Overall, our study added knowledge in rice straw management through a microbial consortium for better utilization in predominantly rice-growing countries. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-03982-z.